Gleyber Torres

2B Detroit Tigers

Age 30 R/R 5'10" / 205 lbs MLB HR -8% Svc 8.942 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	27	MLBNYY	665	.257/.334/.378	15	4	100	1.2
2025	28	MLBDET	628	.256/.362/.387	16	4	119	2.9
2026	29	MLBDET	420	.260/.366/.363	8	0	112	1.7
2027PROJ	30	MLBDET	431	.249/.348/.367	10	2	109	1.3
2028PROJ	31	MLBDET	560	.244/.343/.356	12	3	105	1.2
2029PROJ	32	MLBDET	545	.238/.336/.341	11	2	99	0.7

Last 3 seasons WAR 5.8 · Next 3 projected WAR 3.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.942First FA2028

2027Ext / FA-deal$12M

Skills · percentileStatcast 2024-2026

xwOBA73

Avg EV42

Barrel%40

Bat Spd12

Speed10

Form.239/.344/.333 ▼▼ rolling true talent (60d window) · proj .253/.349/.375

CompsJ.P. Crawford (age 29) · Logan Forsythe (age 31) · A.J. Ellis (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 114109vR 95

AVG/OBP/SLG.249 / .348 / .367

PA431

HR10

K%18

BB%13

BABIP289

ISO121

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

530.254

POWER

Barrel%

406.9

Avg EV

4288.5

Bat Spd

1267.2

SPEED

Sprint

1025.3

Recent Formrolling true talent ⓘ

K%21%▼▼23% over 83 PA (60d) · proj 18%

BB%13%▲14% over 83 PA (60d) · proj 12%

ISO.093▼.028 over 71 AB (60d) · proj .122

HR/BB2.3%▼0.0% over 52 BBE (60d) · proj 3.4%

BABIP.297·.346 over 52 BIP (60d) · proj .294

SLASH.239/.344/.333▼▼proj .253/.349/.375

Platoon Splits2024-2026 · 1411 PA

vs LHP

vs RHP

Edge

369

1042

—

wRC+

136

◀◀L

wOBA

369

308

◀◀L

ISO

200

093

◀◀L

BABIP

284

297

▶R

17.3%

18.5%

◀L

BB%

14.9%

11.1%

◀◀L

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status FA

MLB Debut 2018

Service 8.942 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$12M	+1.5	$12M	+$0.4M
Totals		$12M		$12M	+$0.4M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2014	17	ROK	AZL Cubs	—	183	154	43	6	3	1	25	33	0	8	7	279	380	377	757	97	339	18	14	338	63	—	—	—	—	—	—
2015	18	A+	Myrtle Beach Pelicans	—	24	23	4	0	0	0	1	7	0	0	1	174	208	174	382		250	29	4	180	-15	—	—	—	—	—	—
2015	18	A	South Bend Cubs	—	514	464	136	24	5	3	43	108	2	22	13	293	356	386	741	93	373	21	8	332	71	—	—	—	—	—	—
2016	19	A+	Tampa Yankees	—	547	478	129	29	5	11	58	110	5	21	13	270	355	421	775	151	330	20	11	344	88	—	—	—	—	—	—
2016	19	INTL	Scottsdale Scorpions	—	76	62	25	4	1	3	14	8	0	4	2	403	513	645	1.158	242	431	11	18	502	226	—	—	—	—	—	—
2017	20	AAA	Scranton/Wilkes-Barre RailRiders	—	96	81	25	4	1	2	13	26	1	2	2	309	411	457	867	148	426	27	14	385	112	—	—	—	—	—	—
2017	20	AA	Trenton Thunder	—	139	121	33	10	1	5	17	21	1	5	4	273	367	496	863	223	295	15	12	380	107	—	—	—	—	—	—
2018	21	MLB	New York Yankees	—	484	431	117	16	1	24	42	122	5	6	2	271	343	480	823	209	321	25	9	359	122	+13	+0	-4	+2	+10	2.3
2018	21	AAA	Scranton/Wilkes-Barre RailRiders	—	56	49	17	3	1	1	5	10	0	1	1	347	407	510	918	163	400	18	9	391	129	—	—	—	—	—	—
2019	22	MLB	New York Yankees	—	604	546	152	26	0	38	48	129	3	5	2	278	340	535	875	256	296	21	8	377	134	+24	+0	-7	+6	+13	3.8
2020	23	MLB	New York Yankees	—	160	136	33	8	0	3	22	28	2	1	0	243	356	368	724	125	286	18	14	333	110	+2	+0	+0	+2	+3	0.8
2021	24	MLB	New York Yankees	—	516	459	119	22	0	9	50	104	1	14	6	259	333	366	699	107	314	20	10	314	97	-2	+0	-4	+6	+11	1.2
2022	25	MLB	New York Yankees	—	572	526	135	28	1	24	39	129	3	10	5	257	312	451	762	194	295	23	7	334	107	+5	+0	+0	+2	+12	2.0
2022	25	INTL	Leones del Caracas	—	52	45	13	1	0	1	6	7	0	1	0	289	373	378	750	89	316	13	12	337	114	—	—	—	—	—	—
2023	26	MLB	New York Yankees	—	672	596	163	28	2	25	67	98	3	13	6	273	350	453	803	180	288	15	10	354	123	+18	+0	-2	+2	+15	3.4
2024	27	MLB	New York Yankees	—	665	587	151	26	0	15	65	136	3	4	3	257	334	378	713	121	306	20	10	318	100	+0	-0	-4	+2	+14	1.2
2025	28	MLB	Detroit Tigers	—	628	532	136	22	0	16	85	101	4	4	1	256	362	387	750	132	284	16	14	338	119	+14	+0	-2	+2	+14	2.9
2026	29	MLB	Detroit Tigers	—	420	358	93	13	0	8	57	81	3	0	0	260	366	363	729	103	314	19	14	334	112	+6	+0	+0	+1	+9	1.7
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4721	4171	1099	189	4	162	475	928	27	57	25	263	343	427	770	164	300	20	10	341	117	+96	+1	-22	+26	+102	20.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	17	ROK MLE	AZL Cubs	—	183	163	37	5	2	1	16	48	0	8	7	227	296	301	597	74	288	26	9	262	63	—	—	—	—	—	—
2015	18	A+ MLE	Myrtle Beach Pelicans	—	24	23	3	0	0	0	1	10	0	0	1	130	167	130	297		253	42	4	146	-15	—	—	—	—	—	—
2015	18	A MLE	South Bend Cubs	—	514	477	118	18	4	2	30	149	2	22	13	247	295	314	609	67	349	29	6	273	71	—	—	—	—	—	—
2016	19	A+ MLE	Tampa Yankees	—	547	492	119	29	4	11	44	158	5	21	13	242	311	384	695	142	325	29	8	299	88	—	—	—	—	—	—
2017	20	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	96	85	24	4	1	1	9	31	1	2	2	282	358	388	746	106	420	32	9	333	112	—	—	—	—	—	—
2017	20	AA MLE	Trenton Thunder	—	139	125	30	9	1	4	13	25	1	5	4	240	317	424	741	184	279	18	9	327	107	—	—	—	—	—	—
2018	21	MLB MLE	New York Yankees	—	484	434	115	16	1	22	39	122	5	6	2	265	333	459	791	194	321	25	8	349	122	+13	+0	-4	+2	+10	2.3
2018	21	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	56	50	17	3	1	1	4	12	0	1	1	340	389	500	889	160	371	21	7	359	129	—	—	—	—	—	—
2019	22	MLB MLE	New York Yankees	—	604	549	150	26	0	36	45	129	3	5	2	273	332	517	849	244	296	21	7	366	134	+24	+0	-7	+6	+13	3.8
2020	23	MLB MLE	New York Yankees	—	160	136	33	8	0	3	22	28	2	1	0	243	356	368	724	125	286	18	14	331	110	+2	+0	+0	+2	+3	0.8
2021	24	MLB MLE	New York Yankees	—	516	460	118	22	0	8	49	104	1	14	6	257	329	357	686	100	314	20	9	311	97	-2	+0	-4	+6	+11	1.2
2022	25	MLB MLE	New York Yankees	—	572	528	133	28	1	22	37	129	3	10	5	252	305	434	738	182	295	23	6	327	107	+5	+0	+0	+2	+12	2.0
2023	26	MLB MLE	New York Yankees	—	672	596	161	28	2	23	67	98	3	13	6	270	347	440	786	169	288	15	10	350	123	+18	+0	-2	+2	+15	3.4
2024	27	MLB MLE	New York Yankees	—	665	587	150	26	0	14	65	136	3	4	3	256	333	371	704	116	306	20	10	316	100	+0	-0	-4	+2	+14	1.2
2025	28	MLB MLE	Detroit Tigers	—	628	532	139	23	0	17	85	101	4	4	1	261	367	400	768	139	284	16	14	344	119	+14	+0	-2	+2	+14	2.9
2026	29	MLB MLE	Detroit Tigers	—	420	361	94	13	0	8	54	81	3	0	0	260	361	363	724	102	314	19	13	334	112	+6	+0	+0	+1	+9	1.7
2014	17	ROK MLE	AZL Cubs	—	183	163	37	5	2	1	16	48	0	8	7	227	296	301	597	74	305	26	9	262	63	—	—	—	—	—	—
2014	17	ROK RAW	AZL Cubs	—	183	154	43	6	3	1	25	33	0	8	7	279	380	377	757	97	339	18	14	338	63	—	—	—	—	—	—
2015	18	A MLE	2 teams	—	538	500	122	18	4	2	31	159	2	22	14	244	291	308	599	64	350	30	6	267	67	—	—	—	—	—	—
2015	18	A RAW	2 teams	—	538	487	140	24	5	3	44	115	2	22	14	287	349	376	725	88	367	21	8	325	67	—	—	—	—	—	—
2016	19	A+ MLE	2 teams	—	623	562	134	33	4	12	50	180	5	25	15	238	306	375	682	137	329	29	8	299	88	—	—	—	—	—	—
2016	19	A+ RAW	2 teams	—	623	540	154	33	6	14	72	118	5	25	15	285	374	446	821	161	342	19	12	364	88	—	—	—	—	—	—
2017	20	AA MLE	2 teams	—	235	211	56	13	2	6	21	57	2	7	6	265	338	431	769	166	336	24	9	329	109	—	—	—	—	—	—
2017	20	AA RAW	2 teams	—	235	202	58	14	2	7	30	47	2	7	6	287	385	480	865	193	342	20	13	382	109	—	—	—	—	—	—
2018	21	MLB MLE	2 teams	—	540	484	132	19	2	23	43	134	5	7	3	273	338	463	801	190	326	25	8	350	123	+15	+0	-4	+2	+12	2.6
2018	21	MLB RAW	2 teams	—	540	480	134	19	2	25	47	132	5	7	3	279	350	483	833	204	330	24	9	363	123	+15	+0	-4	+2	+12	2.6
2019	22	MLB MLE	New York Yankees	—	604	549	150	26	0	36	45	129	3	5	2	273	332	517	849	244	292	21	7	366	134	+24	+0	-7	+6	+13	3.8
2019	22	MLB RAW	New York Yankees	—	604	546	152	26	0	38	48	129	3	5	2	278	340	535	875	256	296	21	8	377	134	+24	+0	-7	+6	+13	3.8
2020	23	MLB MLE	New York Yankees	—	160	136	33	8	0	3	22	28	2	1	0	243	356	368	724	125	286	18	14	331	110	+2	+0	+0	+2	+3	0.8
2020	23	MLB RAW	New York Yankees	—	160	136	33	8	0	3	22	28	2	1	0	243	356	368	724	125	286	18	14	333	110	+2	+0	+0	+2	+3	0.8
2021	24	MLB MLE	New York Yankees	—	516	460	118	22	0	8	49	104	1	14	6	257	329	357	686	100	312	20	9	311	97	-2	+0	-4	+6	+11	1.2
2021	24	MLB RAW	New York Yankees	—	516	459	119	22	0	9	50	104	1	14	6	259	333	366	699	107	314	20	10	314	97	-2	+0	-4	+6	+11	1.2
2022	25	MLB MLE	2 teams	—	624	576	146	31	1	25	40	141	3	11	5	253	305	441	746	188	292	23	6	327	107	+6	+0	+0	+2	+14	2.2
2022	25	MLB RAW	2 teams	—	624	571	148	29	1	25	45	136	3	11	5	259	317	445	761	186	297	22	7	334	107	+6	+0	+0	+2	+14	2.2
2023	26	MLB MLE	New York Yankees	—	672	596	161	28	2	23	67	98	3	13	6	270	347	440	786	169	287	15	10	350	123	+18	+0	-2	+2	+15	3.4
2023	26	MLB RAW	New York Yankees	—	672	596	163	28	2	25	67	98	3	13	6	273	350	453	803	180	288	15	10	354	123	+18	+0	-2	+2	+15	3.4
2024	27	MLB MLE	New York Yankees	—	665	587	150	26	0	14	65	136	3	4	3	256	333	371	704	116	306	20	10	316	100	+0	-0	-4	+2	+14	1.2
2024	27	MLB RAW	New York Yankees	—	665	587	151	26	0	15	65	136	3	4	3	257	334	378	713	121	306	20	10	318	100	+0	-0	-4	+2	+14	1.2
2025	28	MLB MLE	Detroit Tigers	—	628	532	139	23	0	17	85	101	4	4	1	261	367	400	768	139	290	16	14	344	119	+14	+0	-2	+2	+14	2.9
2025	28	MLB RAW	Detroit Tigers	—	628	532	136	22	0	16	85	101	4	4	1	256	362	387	750	132	284	16	14	338	119	+14	+0	-2	+2	+14	2.9
2026	29	MLB MLE	Detroit Tigers	—	420	361	94	13	0	8	54	81	3	0	0	260	361	363	724	102	314	19	13	334	112	+6	+0	+0	+1	+9	1.7
2026	29	MLB RAW	Detroit Tigers	—	420	358	93	13	0	8	57	81	3	0	0	260	366	363	729	103	314	19	14	334	112	+6	+0	+0	+1	+9	1.7
2014	17	ROK MLE	AZL Cubs	—	183	165	37	5	2	1	16	48	0	8	7	224	296	297	593	73	288	26	9	262	63	—	—	—	—	—	—
2015	18	A MLE	2 teams	—	538	500	122	18	4	2	31	159	2	22	14	244	291	308	599	64	345	30	6	267	67	—	—	—	—	—	—
2016	19	A+ MLE	2 teams	—	623	563	134	33	4	12	50	180	5	25	15	238	306	375	681	137	325	29	8	299	88	—	—	—	—	—	—
2017	20	AA MLE	2 teams	—	235	210	56	13	2	6	21	57	2	7	6	267	338	433	771	167	337	24	9	329	109	—	—	—	—	—	—
2018	21	MLB MLE	2 teams	—	540	487	132	19	2	23	43	134	5	7	3	271	338	460	798	189	326	25	8	350	123	—	—	—	—	—	—
2019	22	MLB MLE	New York Yankees	—	604	551	150	26	0	36	45	129	3	5	2	272	332	515	847	243	296	21	7	366	134	—	—	—	—	—	—
2020	23	MLB MLE	New York Yankees	—	160	135	33	8	0	3	22	28	2	1	0	244	356	370	727	126	286	18	14	331	110	—	—	—	—	—	—
2021	24	MLB MLE	New York Yankees	—	516	461	118	22	0	8	49	104	1	14	6	256	329	356	685	100	314	20	9	311	97	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	624	576	146	31	1	25	40	141	3	11	5	253	305	441	746	188	295	23	6	327	107	—	—	—	—	—	—
2023	26	MLB MLE	New York Yankees	—	672	597	161	28	2	23	67	98	3	13	6	270	347	439	786	169	288	15	10	350	123	—	—	—	—	—	—
2024	27	MLB MLE	New York Yankees	—	665	592	150	26	0	14	65	136	3	4	3	253	333	368	701	115	306	20	10	316	100	—	—	—	—	—	—
2025	28	MLB MLE	Detroit Tigers	—	628	534	139	23	0	17	85	101	4	4	1	260	367	399	766	139	284	16	14	344	119	—	—	—	—	—	—
2026	29	MLB MLE	Detroit Tigers	—	420	360	94	13	0	8	54	81	3	0	0	261	361	364	725	103	314	19	13	334	112	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	New York Yankees	—	665	592	150	26	0	14	65	136	3	4	3	253	333	368	701	115	306	20	10	316	100	—	—	—	—	—	—
2025	28	MLB MLE	Detroit Tigers	—	628	534	139	23	0	17	85	101	4	4	1	260	367	399	766	139	284	16	14	344	119	—	—	—	—	—	—
2026	29	MLB MLE	Detroit Tigers	—	420	360	94	13	0	8	54	81	3	0	0	261	361	364	725	103	314	19	13	334	112	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	DET	100%	508	437	111	18	0	12	63	93	3	3	1	253	352	375	727	122	294	18	12	330	109	+6	+0	-3	+2	+11	1.5
▸ 2027 — real world (MLB)
2027	30	MLB CTX	DET	100%	431	371	93	15	0	10	54	79	3	2	1	249	348	367	715	118	289	18	13	325	109	+5	+0	-3	+2	+9	1.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	DET	100%	560	483	120	19	0	12	69	105	3	3	1	248	347	364	711	116	290	19	12	323	105	+3	+0	-6	+2	+12	1.2
2029	32	MLB MLE	DET	100%	545	470	113	17	0	11	67	104	3	2	0	242	340	349	689	108	285	19	12	315	99	-1	+0	-7	+2	+12	0.7
2030	33	MLB MLE	DET	100%	445	386	90	13	0	8	54	88	2	1	0	234	331	332	663	98	279	20	12	304	92	-4	+0	-7	+2	+10	0.0
2031	34	MLB MLE	DET	100%	294	256	58	8	0	5	35	60	1	1	0	224	321	312	633	88	272	20	12	292	84	-6	+0	-7	+1	+6	-0.5
2028	31	MLB CTX	DET	100%	560	483	117	18	0	12	69	105	3	3	1	244	343	356	698	112	286	19	12	318	105	+3	+0	-6	+2	+12	1.2
2029	32	MLB CTX	DET	100%	545	470	112	17	0	11	67	104	3	2	0	238	336	341	677	104	281	19	12	310	99	-1	+0	-7	+2	+12	0.7
2030	33	MLB CTX	DET	100%	445	386	89	13	0	8	54	88	2	1	0	230	328	325	653	95	275	20	12	300	92	-4	+0	-7	+2	+10	0.0
2031	34	MLB CTX	DET	100%	294	256	57	8	0	5	35	60	1	1	0	221	317	305	623	85	267	20	12	288	84	-6	+0	-7	+1	+6	-0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6565	5766	1474	245	4	198	700	1285	36	64	26	256	340	403	742	147	294	20	11	331	104	+89	+2	-48	+33	+142	22.2
/ 162G	—	A+C		—	650	571	146	24	0	20	69	127	4	6	3	256	340	403	743	147	294	20	11	331	104	+9	+0	-5	+3	+14	2.2
Career	—	MLE		—	8683	7683	1947	337	17	224	867	1832	48	130	70	253	333	389	722	136	303	21	10	323	104	+93	+2	-51	+35	+152	23.6
/ 162G	—	MLE		—	650	575	145	25	1	17	65	137	4	10	5	252	332	388	720	136	300	21	10	323	104	+9	+0	-5	+3	+14	2.2

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2018 AAAScranton/Wilkes-Barre RailRiders · 56 PAwOBA .395 → .359 (−36)K% 17.9% → 21.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.86%	÷1.002	×1.200	—	—	21.40%
BB% (unintentional) /PA	8.93%	÷1.034	×0.690	—	×1.050	6.25%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	30.77%	÷1.032	×0.930	—	×1.050	29.12%
Doubles /BIP	7.69%	÷1.004	×0.830	—	×1.050	6.68%
Triples /BIP	2.56%	÷1.130	×0.970	—	×1.050	2.31%
Home runs /BIP	2.56%	÷1.046	×0.840	—	×1.050	2.16%

Factors used: league row IL. Park (home-season share, regressed): HR 109, 1B 106, 2B 101, 3B 126, K 100, BB 107 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average).

Result: wOBA .395 → .359; ISO .163 → .147; BABIP .400 → .371. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2017 AATrenton Thunder · 139 PAwOBA .370 → .327 (−43)K% 15.1% → 18.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.11%	÷1.007	×1.220	—	—	18.31%
BB% (unintentional) /PA	12.23%	÷0.979	×0.700	—	×1.050	9.19%
HBP% /PA	0.72%	—	×0.850	—	×1.050	0.64%
Singles /BIP	17.00%	÷1.020	×0.970	×0.972	×1.050	16.51%
Doubles /BIP	10.00%	÷0.936	×0.860	×0.972	×1.050	9.38%
Triples /BIP	1.00%	÷1.150	×0.950	×0.972	×1.050	0.84%
Home runs /BIP	5.00%	÷0.960	×0.780	—	×1.050	4.27%

Factors used: league row EL. Park (home-season share, regressed): HR 92, 1B 104, 2B 87, 3B 130, K 101, BB 96 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.972.

Result: wOBA .370 → .327; ISO .223 → .197; BABIP .295 → .279. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2017 AAAScranton/Wilkes-Barre RailRiders · 96 PAwOBA .380 → .333 (−46)K% 27.1% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.08%	÷0.995	×1.200	—	—	32.67%
BB% (unintentional) /PA	13.54%	÷1.105	×0.690	—	×1.050	8.88%
HBP% /PA	1.04%	—	×0.940	—	×1.050	1.03%
Singles /BIP	32.73%	÷0.980	×0.930	×1.020	×1.050	33.28%
Doubles /BIP	7.27%	÷0.951	×0.830	×1.020	×1.050	6.80%
Triples /BIP	1.82%	÷1.150	×0.970	×1.020	×1.050	1.64%
Home runs /BIP	3.64%	÷1.247	×0.840	—	×1.050	2.57%

Factors used: league row IL. Park (home-season share, regressed): HR 149, 1B 96, 2B 90, 3B 130, K 99, BB 121 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.020.

Result: wOBA .380 → .333; ISO .148 → .121; BABIP .426 → .420. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2016 A+Tampa Yankees · 547 PAwOBA .336 → .299 (−37)K% 20.1% → 28.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.11%	÷0.988	×1.420	—	—	28.89%
BB% (unintentional) /PA	10.60%	÷1.021	×0.750	—	×1.042	8.11%
HBP% /PA	0.91%	—	×0.930	—	×1.042	0.89%
Singles /BIP	22.83%	÷1.022	×0.920	×1.027	×1.042	21.98%
Doubles /BIP	7.88%	÷0.953	×0.960	×1.027	×1.042	8.49%
Triples /BIP	1.36%	÷1.032	×0.810	×1.027	×1.042	1.14%
Home runs /BIP	2.99%	÷0.862	×0.880	—	×1.042	3.18%

Factors used: league row FSL. Park (home-season share, regressed): HR 72, 1B 104, 2B 91, 3B 106, K 98, BB 104 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.027.

Result: wOBA .336 → .299; ISO .151 → .144; BABIP .330 → .325. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2015 ASouth Bend Cubs · 514 PAwOBA .326 → .273 (−53)K% 21.0% → 29.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.01%	÷0.984	×1.360	—	—	29.05%
BB% (unintentional) /PA	8.17%	÷1.006	×0.690	—	×1.045	5.86%
HBP% /PA	0.39%	—	×0.780	—	×1.045	0.32%
Singles /BIP	29.21%	÷1.036	×0.920	×1.042	×1.045	28.27%
Doubles /BIP	6.74%	÷1.109	×0.830	×1.042	×1.045	5.49%
Triples /BIP	1.40%	÷1.073	×0.910	×1.042	×1.045	1.30%
Home runs /BIP	0.84%	÷1.064	×0.800	—	×1.045	0.66%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 113, 1B 107, 2B 122, 3B 115, K 97, BB 101 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.042.

Result: wOBA .326 → .273; ISO .093 → .072; BABIP .373 → .349. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2015 A+Myrtle Beach Pelicans · 24 PAwOBA .175 → .146 (−29)K% 29.2% → 40.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.17%	÷1.025	×1.420	—	—	40.40%
BB% (unintentional) /PA	4.17%	÷0.960	×0.630	—	×1.050	2.87%
HBP% /PA	0.00%	—	×0.860	—	×1.050	0.00%
Singles /BIP	25.00%	÷0.977	×0.940	—	×1.050	25.26%
Doubles /BIP	0.00%	÷1.015	×0.830	—	×1.050	0.00%
Triples /BIP	0.00%	÷1.138	×0.800	—	×1.050	0.00%
Home runs /BIP	0.00%	÷0.888	×0.900	—	×1.050	0.00%

Factors used: league row CAR. Park (home-season share, regressed): HR 78, 1B 95, 2B 103, 3B 128, K 105, BB 92 — applied at half strength. Age: age 19 vs a level average of 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average).

Result: wOBA .175 → .146; ISO .000 → .000; BABIP .250 → .253. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2014 ROKAZL Cubs · 183 PAwOBA .338 → .262 (−76)K% 18.0% → 26.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.03%	÷1.000	×1.440	—	—	25.97%
BB% (unintentional) /PA	13.66%	÷1.000	×0.620	—	×1.022	8.66%
HBP% /PA	0.00%	—	×0.720	—	×1.022	0.00%
Singles /BIP	27.27%	÷1.000	×0.820	×1.044	×1.022	23.87%
Doubles /BIP	4.96%	÷1.000	×0.720	×1.044	×1.022	3.81%
Triples /BIP	2.48%	÷1.000	×0.720	×1.044	×1.022	1.91%
Home runs /BIP	0.83%	÷1.000	×0.780	—	×1.022	0.66%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.044.

Result: wOBA .338 → .262; ISO .097 → .075; BABIP .339 → .288. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Asdrúbal Cabreralast yr '21 career totals — 15 seasons, 7,401 PA	11.1	7,401	195	91	266	329	423	+58	+11	38.2	32.2
/162	664	17	8	+5.2	+1.0	3.4	pk7: 26
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 14 projected seasons	10.5	6,996	209	66	257	338	404	+25	-23	30.6	26.3
/162	664	20	6	+2.4	-2.2	2.9	pk7: 22
#2Edgardo Alfonzo'95-'06 * career totals — 12 seasons, 6,108 PA	9.2	6,108	146	53	273*	342*	413*	+22	-38	23.8	24.6
/162	664	16	6	+2.4	-4.1	2.6	pk7: 25
#3Rickie Weeks Jr.last yr '17 career totals — 13 seasons, 5,098 PA	7.7	5,098	161	132	246	344	420	+12	-40	23.3	22.4
/162	664	21	17	+1.5	-5.2	3.0	pk7: 22
#4Denis Menke'62-'74 * career totals — 12 seasons, 5,934 PA	8.9	5,934	101	34	250*	346*	403*	+30	-23	22.7	21.7
/162	664	11	4	+3.4	-2.6	2.5	pk7: 21
#5Kelly Johnsonlast yr '16 career totals — 11 seasons, 5,139 PA	7.7	5,139	155	87	251	330	422	+8	-3	22.3	21.3
/162	664	20	11	+1.0	-0.4	2.9	pk7: 20
#6Davey Johnson'65-'78 * career totals — 12 seasons, 5,465 PA	8.2	5,465	136	33	267*	345*	449*	+10	-28	22.8	20.8
/162	664	17	4	+1.3	-3.5	2.8	pk7: 19

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Gleyber Torres (OGILVIE)	30	—	—	—	—	251/349/372	121	294	10	2	18%	12%	109	+1.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●J.P. Crawford 2024 · MLB	29	54→57	46→45	42→50	60	261/356/399	138	300	13	3	17%	12%	117	+2.6	242/338/373	131	289	14	6	20%	12%	105	+1.7	233/331/352	119	279	14	5	20%	12%	98	+1.1
✕Logan Forsythe 2018 · MLB	31	51→57	48→50	42→50	55	249/342/395	146	310	15	7	23%	11%	112	+2.2	230/320/336	106	300	9	5	24%	11%	89	+0.5	226/315/312	87	295	7	4	23%	11%	81	-0.1
✕A.J. Ellis 2013 · MLB	32	52→54	44→45	41→40	57	254/348/376	122	301	12	2	19%	11%	109	+2.0	232/325/351	119	271	12	2	18%	11%	95	+1.0	219/320/329	110	252	11	0	17%	12%	91	+0.4
✕Frank Menechino 2002 · MLB	31	50→49	48→55	38→40	61	244/359/389	145	283	14	4	19%	13%	117	+2.6	238/349/378	140	275	14	4	18%	13%	110	+2.1	263/357/422	158	305	14	2	17%	11%	122	+1.0
✕Trevor Plouffe 2016 · MLB	30	49→54	52→60	45	50	249/313/422	173	285	18	3	20%	8%	106	+1.8	231/295/391	160	274	19	4	23%	8%	93	+0.8	213/282/363	150	256	20	3	25%	8%	82	+0.0
✕Curt Casali 2020 · MLB	31	49	48→50	40→30	48	244/309/380	137	296	16	3	23%	8%	95	+1.0	230/320/392	162	298	19	5	28%	10%	103	+1.5	207/312/292	85	276	8	0	25%	11%	77	-0.1
✕Kevin Plawecki 2021 · MLB	30	51→59	46→45	46→30	49	249/320/387	138	293	13	5	19%	8%	101	+1.4	248/310/353	105	293	9	4	18%	7%	89	+0.5	238/300/320	82	288	6	0	19%	7%	76	-0.1
✕Ronny Paulino 2011 · MLB	30	52→62	45→50	46→40	49	256/308/382	125	294	12	4	17%	7%	95	+0.9	248/290/344	96	296	7	3	18%	6%	78	-0.3	252/294/346	94	300	8	0	18%	6%	79	-0.1
✕Stephen Drew 2013 · MLB	30	48→57	47→55	44→45	53	240/312/383	144	286	13	6	21%	10%	97	+1.1	217/289/378	161	261	16	5	23%	9%	88	+0.4	217/288/392	175	232	21	0	17%	9%	92	+0.3
✕Carson Kelly 2024 · MLB	30	45→52	46→55	49→40	51	224/301/355	130	269	14	5	22%	9%	87	+0.4	243/319/387	144	279	18	3	19%	9%	101	+1.4	248/328/392	144	277	19	1	18%	9%	106	+1.1
●David Bell 2003 · MLB	30	50→57	50	40	52	254/316/411	157	264	18	3	13%	8%	105	+1.7	249/320/388	139	266	14	2	12%	9%	101	+1.4	263/328/396	133	283	13	1	12%	8%	106	+1.8
✕Manny Piña 2017 · MLB	30	51	45→55	44→40	46	249/297/374	125	285	12	5	18%	6%	89	+0.5	255/308/397	142	307	15	5	21%	6%	99	+1.2	255/313/402	147	309	16	3	22%	6%	103	+0.7
✕Austin Nola 2020 · MLB	30	49→52	46→45	48→45	49	244/312/377	133	296	14	6	22%	8%	96	+1.0	257/328/392	135	300	13	5	18%	8%	105	+1.7	259/334/370	111	295	10	1	15%	8%	103	+0.7
✕Elias Díaz 2021 · MLB	30	51→59	44→50	44→45	49	249/304/360	111	287	11	3	18%	7%	88	+0.5	236/293/387	151	270	18	2	19%	7%	91	+0.7	236/292/382	147	273	17	0	20%	7%	91	+0.5
✕Josh Phegley 2018 · MLB	30	46→50	48→60	42→40	47	233/293/382	149	265	15	4	19%	6%	90	+0.6	223/280/378	155	261	17	3	21%	6%	84	+0.2	218/272/377	159	253	18	0	22%	5%	82	+0.0
●Jhonny Peralta 2011 · MLB	29	51→61	48→55	43→40	50	255/315/402	147	293	15	2	19%	8%	102	+1.5	271/326/431	160	311	17	2	18%	8%	113	+2.3	275/337/435	160	317	18	2	19%	8%	119	+2.6
✕Daniel Descalso 2017 · MLB	30	47→56	45→50	44→45	53	233/307/357	124	274	13	6	20%	10%	89	+0.5	225/322/378	153	280	16	5	24%	12%	100	+1.3	209/318/360	151	265	16	3	25%	13%	96	+0.6
✕Tucker Barnhart 2020 · MLB	29	48→53	46→45	41→40	53	239/314/370	132	281	14	3	20%	10%	95	+0.9	234/307/358	124	296	13	3	24%	9%	90	+0.6	230/300/327	97	301	9	0	25%	8%	80	-0.1
✕Jamie Westbrook 2024 · AAA	29	48→54	47→50	42→45	50	241/312/371	130	279	15	5	19%	8%	95	+0.9	234/300/356	122	281	12	5	20%	7%	87	+0.4	228/295/342	115	275	10	2	20%	7%	80	-0.1
✕Michael McKenry 2016 · MLB	31	48→47	50→55	43→40	53	241/325/403	161	293	17	8	23%	10%	107	+1.8	206/298/335	129	283	12	6	29%	11%	82	-0.0	175/275/285	109	248	10	2	31%	11%	60	-0.7

Gleyber Torres

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps